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Lund University
Master's Programme in Data Analytics and Business Economics
<p>Transforming data into insights that can enhance decision-making is a key challenge for companies of every size, across all industries. In this programme, you will learn how to work the numbers, draw conclusions, and communicate your results. </p><p>Have you noticed how Netflix and YouTube send you suggestions ba…
- Higher education
- Information unavailable
- 31 August 2026
- Lund
- Information unavailable
- 100 %
Overview
<p>Transforming data into insights that can enhance decision-making is a key challenge for companies of every size, across all industries. In this programme, you will learn how to work the numbers, draw conclusions, and communicate your results. </p><p>Have you noticed how Netflix and YouTube send you suggestions based on your previous views? How Spotify makes suggestions based on what you have listened to in the past? How Amazon shows similar products that you might be interested in based on previous purchases? </p><p>These are companies that are known for their use of “big data” and analytics to predict and steer customer behaviour. Today, most organisations are heavily reliant on big data and need to harness the information their data provides and to use it to improve their operations. Organisations are searching for analytically talented individuals with statistical and programming skills that also understand the business-economic context, as well as the relevant legal and ethical boundaries. This multidisciplinary programme is designed to solve business problems by integrating statistics, economics, business, informatics and law. Close collaboration with our dedicated private sector advisors ensures that the programme provides relevant competences and meets the demands of the labour market. </p><p><br/></p><p> </p>
Admission scores
Entry requirements
An undergraduate degree (BA/BSc) of at least three years, 180 credits, in a subject matter including quantitative methods. More specifically, it is required that the students have: an undergraduate degree including one of the following: - at least 30 credits in statistics and mathematics with at least one course in statistics that includes regression analysis and one course in mathematics; - at least 60 credits in economics, informatics or business administration with at least one course in econometrics or regression analysis and one course in statistics or mathematics; - at least 60 credits in statistics with at least one course in regression analysis, English course 6 (advanced proficiency) For applicants not having a course named regression analysis or econometrics, it is important to include a course syllabus (or something similar) in the application, to demonstrate the fulfilment of this specific requirement. It is recommended that students have at least 10 credits in economics and 10 credits in business administration.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.lu.eagda.18270.20262
- Last checked
- 2026-09-23T10:38:26.989764+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
Application and important dates
- Programme or course starts
- Programme or course ends
Salary and salary distribution
Common occupations after graduation
Students
Geographical background
Previous upper-secondary schools and programmes
Completion and outcomes
About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.eagda.18270.20262
- Offering identity in the source
- e.uoh.lu.eagda.18270.20262
- Education-form source code
- HS
- Education code in the source
- EAGDA
- Change time according to the source
- 2026-03-25T09:16:09
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.